Towards a circular economy: insights based on the development of the global ENGAGE-materials model and evidence for the iron and steel industry

A number of recent economic modelling studies have attempted to analyse resource efficiency and the circular economy. However, modelling analysis in this area is relatively underdeveloped. In particular, many CGE models are unable to provide significant insight given their aggregated sectoral coverage. Here we describe the development of the Environmental Global Applied General Equilibrium (ENGAGEmaterials) model created to consider the economic and sectoral effects of potential policies on a circular economy and resource efficiency, which affect materials and resources at the stages of extraction, production and recycling. Our policy scope is global with a special emphasis on China and Europe, as both regions have dedicated policies in place and indicate their willingness to take the lead. The case of steel is relevant as it is a key material for all economies across the world and offers a range of interesting features for circularity and sustainability. ENGAGE-materials models iron ore mining, primary production of iron and steel, secondary production of iron and steel, and steel scrap recycling at the global level. We utilise this technology rich framework to provide preliminary results on scenarios comprising economic insights into a saturation effect and straightforward policy such as doubling the availability of secondary steel

Steel in a circular economy: global implications of a green shift in China

China is increasingly known for its ambitions towards an ‘ecological civilisation’ and a circular economy. Our article assesses the implications of an accelerated shift towards steel recycling in China. Given the relevance of steel for development worldwide as well as its environmental intensity, any such shift is likely to have implications for competitiveness in China and beyond. Recent findings suggest that China could take advantage of an increasing availability of obsolete steel scrap in the coming decades, moving towards more circular, and potentially greener, steel production. We assess such industrial restructuring from an economic perspective and address the competitiveness of China relative to other developing and industrialised regions. The analysis uses a novel global economy-wide modelling framework (ENGAGE-materials) to assess the aggregate and sector-level impacts of different scrap use options in China in the 2019–2030 time frame. The results show moderate GDP gains for China of cumulated USD 589 billion in GDP gains by 2030 despite a replacement of primary steel capacity. A more comprehensive industrial policy mix aimed at improved recycling practices and more adaptive downstream sectors could increase gains to USD 819 billion. The international implications are mixed, with losses for iron ore producers (Australia, Brazil and India) and gains for most developing countries benefiting from lower steel prices. Another result is an increasing demand for coal in electricity production if such a shift wouldn’t be aligned with an accelerated energy transition towards low carbon pathways. We discuss policy implications of such alignment, potential co-benefits, and a need for green international partnerships

Experimental measurements in Hartman oscillators

The paper presents high frequency pointwise measurements of pressure and temperature carried out on a shock wave generator consisting of a couple of supersonic jets impinging on a Hartman oscillator system. The shock wave generator was developed as a means to achieve an aerodynamically controlled pulsed detonation chamber. The analysis allows the selection of the optimal geometry and inlet conditions for such an application. The effect of the inlet conditions and of the geometry of the experimental model on the frequency and amplitude of the pressure waves occurring in the system is analyzed. The paper also presents the effects of other geometrical parameters: the critical section of the jet nozzles, the volume ratio of the resonator geometry, and the inlet angles of the jets. Effects of inlet pressure and temperature are also included

Extrapolation or saturation – revisiting growth patterns, development stages and decoupling

The contemporary debate considering the use of natural resources in economic growth centres around the concept of ‘decoupling’ driven through improvements in resource efficiency. Many studies extrapolate future demand from a short time series of previous years. However, we believe there should be greater attention on the underlying demand assumptions and the possibility of long-term changes. Accordingly, this paper is concerned with a potential saturation in material use as a result of countries moving through stages of development over decades from early industrialisation, over mass production and into a mature stage. An observation of such saturation is relevant for global environmental change as future demand for resources could be lower than currently expected, leading to less associated environmental pressures. In particular, emerging economies are undergoing changing growth patterns, and their future resource use may be significantly lower than contemporary analysis suggests. This paper combines the analytical strands of resource economics and material flow analysis. It investigates both material-specific demand and stock build-up trends over an extended time horizon of a century. Four materials (steel, cement, aluminium and copper) are analysed applying an indicator called ‘Apparent Domestic Consumption’ (ADC) and using international trade data for four industrialised countries (Germany, Japan, UK, USA) together with China as the most preeminent emerging economy. Our results confirm the occurrence of a saturation effect for most materials considered. While the evidence is strong for the per capita apparent consumption of steel, copper and cement in the four industrialised countries, it is somewhat weaker for aluminium. Also, such saturation in material use can start at different income levels, with the saturation beginning to occur relatively early for steel and cement ($12,000 GDP/capita) and later for copper ($20,000 GDP/capita). The results suggest a time gap of around thirty+ years from the take-off of large-scale adoption of one type of material and any saturation occurring. We also shed light on the build-up of stocks in the economy, where our findings suggest there is a delayed saturation of at least twenty years compared to apparent consumption depending on the lifetimes of capital goods. With regard to China, a demand saturation for steel and copper has already started to occur, and our analysis suggests such saturation will soon take place for cement. These findings provide a more moderate outlook on China’s future material demand compared to an extrapolation of recent dynamics. Our new insights on the nexus between economic growth, development stages and the use of natural resources have implications for the decoupling debate and for investments into commodities. From a wider environmental policy perspective, one may expect China and other emerging economies to achieve a saturation effect soon and therefore also peak their industrial emissions of greenhouse gases, supporting the nationally determined contribution (NDC) to the Paris Agreement on Climate Change

A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal-appearing brain tissue

Cancer therapy for both central nervous system (CNS) and non-CNS tumors has been previously associated with transient and long-term cognitive deterioration, commonly referred to as ‘chemo fog’. This therapy-related damage to otherwise normal-appearing brain tissue is reported using post-mortem neuropathological analysis. Although the literature on monitoring therapy effects on structural magnetic resonance imaging (MRI) is well established, such macroscopic structural changes appear relatively late and irreversible. Early quantitative MRI biomarkers of therapy-induced damage would potentially permit taking these treatment side effects into account, paving the way towards a more personalized treatment planning. This systematic review (PROSPERO number 224196) provides an overview of quantitative tomographic imaging methods, potentially identifying the adverse side effects of cancer therapy in normal-appearing brain tissue. Seventy studies were obtained from the MEDLINE and Web of Science databases. Studies reporting changes in normal-appearing brain tissue using MRI, PET, or SPECT quantitative biomarkers, related to radio-, chemo-, immuno-, or hormone therapy for any kind of solid, cystic, or liquid tumor were included. The main findings of the reviewed studies were summarized, providing also the risk of bias of each study assessed using a modified QUADAS-2 tool. For each imaging method, this review provides the methodological background, and the benefits and shortcomings of each method from the imaging perspective. Finally, a set of recommendations is proposed to support future research

CrowdHEALTH: Holistic Health Records and Big Data Analytics for Health Policy Making and Personalized Health.

Today's rich digital information environment is characterized by the multitude of data sources providing information that has not yet reached its full potential in eHealth. The aim of the presented approach, namely CrowdHEALTH, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants. HHRs are transformed into HHRs clusters capturing the clinical, social and human context of population segments and as a result collective knowledge for different factors. The proposed approach also seamlessly integrates big data technologies across the complete data path, providing of Data as a Service (DaaS) to the health ecosystem stakeholders, as well as to policy makers towards a "health in all policies" approach. Cross-domain co-creation of policies is feasible through a rich toolkit, being provided on top of the DaaS, incorporating mechanisms for causal and risk analysis, and for the compilation of predictions

The CrowdHEALTH project and the Hollistic Health Records: Collective Wisdom Driving Public Health Policies.

Introduction: With the expansion of available Information and Communication Technology (ICT) services, a plethora of data sources provide structured and unstructured data used to detect certain health conditions or indicators of disease. Data is spread across various settings, stored and managed in different systems. Due to the lack of technology interoperability and the large amounts of health-related data, data exploitation has not reached its full potential yet. Aim: The aim of the CrowdHEALTH approach, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants defining health status by using big data management mechanisms. Methods: HHRs are transformed into HHRs clusters capturing the clinical, social and human context with the aim to benefit from the collective knowledge. The presented approach integrates big data technologies, providing Data as a Service (DaaS) to healthcare professionals and policy makers towards a "health in all policies" approach. A toolkit, on top of the DaaS, providing mechanisms for causal and risk analysis, and for the compilation of predictions is developed. Results: CrowdHEALTH platform is based on three main pillars: Data & structures, Health analytics, and Policies. Conclusions: A holistic approach for capturing all health determinants in the proposed HHRs, while creating clusters of them to exploit collective knowledge with the aim of the provision of insight for different population segments according to different factors (e.g. location, occupation, medication status, emerging risks, etc) was presented. The aforementioned approach is under evaluation through different scenarios with heterogeneous data from multiple sources

Advanced MR techniques for preoperative glioma characterization: Part 1

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2

A Computational Study of Elongation Factor G (EFG) Duplicated Genes: Diverged Nature Underlying the Innovation on the Same Structural Template

BACKGROUND: Elongation factor G (EFG) is a core translational protein that catalyzes the elongation and recycling phases of translation. A more complex picture of EFG's evolution and function than previously accepted is emerging from analyzes of heterogeneous EFG family members. Whereas the gene duplication is postulated to be a prominent factor creating functional novelty, the striking divergence between EFG paralogs can be interpreted in terms of innovation in gene function. METHODOLOGY/PRINCIPAL FINDINGS: We present a computational study of the EFG protein family to cover the role of gene duplication in the evolution of protein function. Using phylogenetic methods, genome context conservation and insertion/deletion (indel) analysis we demonstrate that the EFG gene copies form four subfamilies: EFG I, spdEFG1, spdEFG2, and EFG II. These ancient gene families differ by their indispensability, degree of divergence and number of indels. We show the distribution of EFG subfamilies and describe evidences for lateral gene transfer and recent duplications. Extended studies of the EFG II subfamily concern its diverged nature. Remarkably, EFG II appears to be a widely distributed and a much-diversified subfamily whose subdivisions correlate with phylum or class borders. The EFG II subfamily specific characteristics are low conservation of the GTPase domain, domains II and III; absence of the trGTPase specific G2 consensus motif "RGITI"; and twelve conserved positions common to the whole subfamily. The EFG II specific functional changes could be related to changes in the properties of nucleotide binding and hydrolysis and strengthened ionic interactions between EFG II and the ribosome, particularly between parts of the decoding site and loop I of domain IV. CONCLUSIONS/SIGNIFICANCE: Our work, for the first time, comprehensively identifies and describes EFG subfamilies and improves our understanding of the function and evolution of EFG duplicated genes